umontreal.iro.lecuyer.probdistmulti
Class BiNormalGenzDist

java.lang.Object
  umontreal.iro.lecuyer.probdistmulti.ContinuousDistributionMulti
      umontreal.iro.lecuyer.probdistmulti.ContinuousDistribution2Dim
          umontreal.iro.lecuyer.probdistmulti.BiNormalDist
              umontreal.iro.lecuyer.probdistmulti.BiNormalGenzDist

public class BiNormalGenzDist
extends BiNormalDist

Extends the class BiNormalDist for the bivariate normal distribution using Genz's algorithm as described in.

Field Summary

Fields inherited from class umontreal.iro.lecuyer.probdistmulti.ContinuousDistribution2Dim

decPrec

Constructor Summary

BiNormalGenzDist(double rho)
Constructs a BiNormalGenzDist object with default parameters μ₁ = μ₂ = 0, σ₁ = σ₂ = 1 and correlation ρ = rho.

BiNormalGenzDist(double mu1, double sigma1, double mu2, double sigma2, double rho)
Constructs a BiNormalGenzDist object with parameters μ₁ = mu1, μ₂ = mu2, σ₁ = sigma1, σ₂ = sigma2 and ρ = rho.

Method Summary

double	barF(double x, double y) .
static double	barF(double x, double y, double rho)
static double	barF(double mu1, double sigma1, double x, double mu2, double sigma2, double y, double rho)
double	cdf(double x, double y) .
static double	cdf(double x, double y, double rho) Computes the standard binormal distribution with the method described in.
static double	cdf(double mu1, double sigma1, double x, double mu2, double sigma2, double y, double rho)

Methods inherited from class umontreal.iro.lecuyer.probdistmulti.BiNormalDist

density, density, density, getCorrelation, getCorrelation, getCovariance, getCovariance, getMean, getMean, getMu1, getMu2, getSigma1, getSigma2

Methods inherited from class umontreal.iro.lecuyer.probdistmulti.ContinuousDistribution2Dim

cdf, density

Methods inherited from class umontreal.iro.lecuyer.probdistmulti.ContinuousDistributionMulti

getDimension

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

BiNormalGenzDist

public BiNormalGenzDist(double rho)

Constructs a BiNormalGenzDist object with default parameters μ₁ = μ₂ = 0, σ₁ = σ₂ = 1 and correlation ρ = rho.

BiNormalGenzDist

public BiNormalGenzDist(double mu1,
                        double sigma1,
                        double mu2,
                        double sigma2,
                        double rho)

Constructs a BiNormalGenzDist object with parameters μ₁ = mu1, μ₂ = mu2, σ₁ = sigma1, σ₂ = sigma2 and ρ = rho.

Method Detail

cdf

public static double cdf(double x,
                         double y,
                         double rho)

Computes the standard binormal distribution with the method described in. The code for the cdf was translated directly from the Matlab code written by Alan Genz and available from his web page at http://www.math.wsu.edu/faculty/genz/homepage (the code is copyrighted by Alan Genz and is included in this package with the kind permission of the author). The absolute error is expected to be smaller than 0.5⋅10^-15.

cdf

public static double cdf(double mu1,
                         double sigma1,
                         double x,
                         double mu2,
                         double sigma2,
                         double y,
                         double rho)

cdf

public double cdf(double x,
                  double y)

Description copied from class: ContinuousDistribution2Dim

. Computes the distribution function F(x, y):

F(x, y) = P[X <= x, Y <= y] = ∫_-∞^xds∫_-∞^ydt f (s, t).

Overrides:

cdf in class BiNormalDist

Parameters:

x - value x at which the distribution function is evaluated

y - value y at which the distribution function is evaluated

Returns:

distribution function evaluated at (x, y)

barF

public double barF(double x,
                   double y)

Description copied from class: ContinuousDistribution2Dim

. Computes the upper cumulative distribution function bar(F)(x, y):

bar(F)(x, y) = P[X >= x, Y >= y] = ∫^∞_xds∫^∞_ydt f (s, t).

Overrides:

barF in class BiNormalDist

Parameters:

x - value x at which the upper distribution is evaluated

y - value y at which the upper distribution is evaluated

Returns:

upper distribution function evaluated at (x, y)

barF

public static double barF(double mu1,
                          double sigma1,
                          double x,
                          double mu2,
                          double sigma2,
                          double y,
                          double rho)

barF

public static double barF(double x,
                          double y,
                          double rho)